Description Usage Format Details Source References Examples

Data about the number of youth homicides in Boston during the ‘Boston Gun Project’—a policing initiative aiming at lowering homicide victimization among young people in Boston.

1 | ```
data("BostonHomicide")
``` |

A data frame containing 6 monthly time series and two factors coding seasonality and year, respectively.

- homicides
time series. Number of youth homicides.

- population
time series. Boston population (aged 25-44), linearly interpolated from annual data.

- populationBM
time series. Population of black males (aged 15-24), linearly interpolated from annual data.

- ahomicides25
time series. Number of adult homicides (aged 25 and older).

- ahomicides35
time series. Number of adult homicides (aged 35-44).

- unemploy
time series. Teen unemployment rate (in percent).

- season
factor coding the month.

- year
factor coding the year.

The ‘Boston Gun Project’ is a policing initiative aiming at lowering youth homicides in Boston. The project began in early 1995 and implemented the so-called ‘Operation Ceasefire’ intervention which began in the late spring of 1996.

Piehl et al. (2004), Figure 1, Figure 3, and Table 1.

From the table it is not clear how the data should be linearly interpolated.
Here, it was chosen to use the given observations for July of the corresponding
year and then use `approx`

with `rule = 2`

.

Piehl A.M., Cooper S.J., Braga A.A., Kennedy D.M. (2003), Testing for Structural
Breaks in the Evaluation of Programs, *The Review of Economics and Statistics*,
**85**(3), 550-558.

Kennedy D.M., Piehl A.M., Braga A.A. (1996), Youth Violence in Boston: Gun Markets,
Serious Youth Offenders, and a Use-Reduction Strategy, *Law and Contemporary Problems*,
**59**, 147-183.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
data("BostonHomicide")
attach(BostonHomicide)
## data from Table 1
tapply(homicides, year, mean)
populationBM[0:6*12 + 7]
tapply(ahomicides25, year, mean)
tapply(ahomicides35, year, mean)
population[0:6*12 + 7]
unemploy[0:6*12 + 7]
## model A
## via OLS
fmA <- lm(homicides ~ populationBM + season)
anova(fmA)
## as GLM
fmA1 <- glm(homicides ~ populationBM + season, family = poisson)
anova(fmA1, test = "Chisq")
## model B & C
fmB <- lm(homicides ~ populationBM + season + ahomicides25)
fmC <- lm(homicides ~ populationBM + season + ahomicides25 + unemploy)
detach(BostonHomicide)
``` |

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